-----------------------------------------------------------------------------------------------------------------------
       log:  Z:\interactionmodels\replication\legislativeparties_replication_xls.log
  log type:  text
 opened on:  10 Jan 2007, 20:01:03

. *     ***************************************************************** *;
. *     ***************************************************************** *;
. *       File-Name:      legislativeparties_replication_xls.do           *;
. *       Date:           01/09/2007                                      *;
. *       Author:         MRG                                             *;
. *       Purpose:        Replicate Mozaffar et al. 2003, table 2         *;
. *       Input File:     XLS_mozaffar.dta                                *;
. *       Output File:    legislativeparties_replication_xls.log          *;
. *       Data Output:    none                                            *;
. *       Previous file:                                                  *;
. *       Machine:                                                        *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. set mem 10m;
(10240k)

. use getdata\XLS_mozaffar.dta;

. *     ****************************************************************  *;
. *           Summary Statistics                                          *;
. *     ****************************************************************  *;
. sum;

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
 country_xls |         0
    year_nyu |        62    1994.081    3.930955       1980       2000
dictator_nyu |        62    .5645161    .4998678          0          1
elecpartie~s |        62    3.234355    2.699867        1.4       14.9
legparties~s |        62    2.340323    1.505894          1        8.8
-------------+--------------------------------------------------------
avemagnitu~s |        62    32.18519    79.66943          1        400
logmag10_xls |        62    .6975806    .7657045          0      2.602
proximity_~s |        62    .6246774    .4255131          0          1
prescandid~s |        62    2.254839    1.489931          0        7.3
prox_presc~s |        62    1.442323    1.177821          0        4.6
-------------+--------------------------------------------------------
fragme~n_xls |        62    4.382419     2.74622          1       9.91
fragme~2_xls |        62    26.62613    28.37423          1      98.21
concentrat~s |        62    1.597258     .963064          0       3.24
frag_conc_~s |        62    8.193395    6.824679          0    25.4664
frag2_conc~s |        62    51.16194    59.53712          0     208.42
-------------+--------------------------------------------------------
    lmgfrgts |        62    21.73133    47.40832          0   182.4051
    lmgconto |        62    1.154228    1.518987          0   5.317299
l~2_conc_xls |        62    34.08677    64.67844          0     265.65
     elf_xls |        56      .62625    .2404281          0        .93
   pregb_xls |        62    .4206452     .281692          0        .82
-------------+--------------------------------------------------------
logmag10_e~s |        62    .4157788    .6017939          0   2.289813
pregb_logm~s |        62    .3235943    .5029105          0   2.003586
  logmag_xls |        62    1.606316    1.763218          0   5.991465
logmag10_c~s |        62    1.154257     1.51896          0    5.31634
l~0_frag_xls |        62    3.311054    5.323039          0   20.52978
-------------+--------------------------------------------------------
logmag10_f.. |        62    5.522605      8.2276          0   33.66884
logmag_con~s |        62    2.657708    3.497597          0   12.24354
l~g_frag_xls |        62     7.62432    12.25799          0   47.27266
logmag_fra.. |        62    12.71621    18.94531          0   77.52715

. *     ****************************************************************  *;
. *       First, try to replicate Model 1 in Table 2, page 386.           *;
. *     ****************************************************************  *;
. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  3,    58) =    5.78
       Model |  31.8297046     3  10.6099015           Prob > F      =  0.0016
    Residual |  106.501091    58   1.8362257           R-squared     =  0.2301
-------------+------------------------------           Adj R-squared =  0.1903
       Total |  138.330795    61  2.26771796           Root MSE      =  1.3551

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .0120857   .2309239     0.05   0.958    -.4501588    .4743302
proximity_~s |  -2.793368   .6762521    -4.13   0.000    -4.147033   -1.439702
prox_presc~s |   .8807476   .2455337     3.59   0.001     .3892585    1.372237
       _cons |   2.806523   .3700445     7.58   0.000     2.065799    3.547248
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  3,    58) =    5.78
       Model |  31.8296735     3  10.6098912           Prob > F      =  0.0016
    Residual |  106.501122    58  1.83622624           R-squared     =  0.2301
-------------+------------------------------           Adj R-squared =  0.1903
       Total |  138.330795    61  2.26771796           Root MSE      =  1.3551

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   .0052321   .1002824     0.05   0.959    -.1955049    .2059691
proximity_~s |   -2.79337   .6762521    -4.13   0.000    -4.147035   -1.439704
prox_presc~s |   .8807437   .2455339     3.59   0.001     .3892541    1.372233
       _cons |   2.806557   .3700435     7.58   0.000     2.065834    3.547279
------------------------------------------------------------------------------

. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    7.64
                                                       Prob > F      =  0.0002
                                                       R-squared     =  0.2301
                                                       Root MSE      =  1.3551

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .0120857   .1258691     0.10   0.924    -.2398687    .2640401
proximity_~s |  -2.793368   .6398755    -4.37   0.000    -4.074217   -1.512518
prox_presc~s |   .8807476    .207705     4.24   0.000     .4649808    1.296514
       _cons |   2.806523   .4709899     5.96   0.000     1.863735    3.749312
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    7.64
                                                       Prob > F      =  0.0002
                                                       R-squared     =  0.2301
                                                       Root MSE      =  1.3551

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   .0052321   .0546582     0.10   0.924    -.1041781    .1146423
proximity_~s |   -2.79337   .6398772    -4.37   0.000    -4.074223   -1.512516
prox_presc~s |   .8807437   .2077035     4.24   0.000       .46498    1.296507
       _cons |   2.806557   .4710021     5.96   0.000     1.863744     3.74937
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Neither of these work                                           *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Model 2                                                         *;
. *     ****************************************************************  *;
. regress legparties_xls fragmentation_xls concentration_xls frag_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  3,    58) =   12.93
       Model |  55.4272508     3  18.4757503           Prob > F      =  0.0000
    Residual |  82.9035445    58  1.42937146           R-squared     =  0.4007
-------------+------------------------------           Adj R-squared =  0.3697
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1956

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~n_xls |  -.3472055   .1101943    -3.15   0.003    -.5677833   -.1266277
concentrat~s |  -.1966835   .2668285    -0.74   0.464    -.7307989    .3374318
frag_conc_~s |   .2558319   .0595583     4.30   0.000     .1366131    .3750507
       _cons |   2.079945   .3987027     5.22   0.000     1.281855    2.878035
------------------------------------------------------------------------------

. regress legparties_xls fragmentation_xls concentration_xls frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    6.81
                                                       Prob > F      =  0.0005
                                                       R-squared     =  0.4007
                                                       Root MSE      =  1.1956

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~n_xls |  -.3472055   .1235835    -2.81   0.007    -.5945847   -.0998263
concentrat~s |  -.1966835   .2669845    -0.74   0.464    -.7311111     .337744
frag_conc_~s |   .2558319   .0837544     3.05   0.003     .0881793    .4234845
       _cons |   2.079945   .2306208     9.02   0.000     1.618308    2.541583
------------------------------------------------------------------------------

. regress legparties_xls fragmentation2_xls concentration_xls frag_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  3,    58) =   10.53
       Model |  48.7831366     3  16.2610455           Prob > F      =  0.0000
    Residual |  89.5476587    58  1.54392515           R-squared     =  0.3527
-------------+------------------------------           Adj R-squared =  0.3192
       Total |  138.330795    61  2.26771796           Root MSE      =  1.2425

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~2_xls |  -.0231894   .0104889    -2.21   0.031    -.0441852   -.0021935
concentrat~s |  -.2169059    .304676    -0.71   0.479    -.8267811    .3929693
frag_conc_~s |   .2154692   .0624248     3.45   0.001     .0905123    .3404261
       _cons |   1.538796   .3363132     4.58   0.000     .8655925       2.212
------------------------------------------------------------------------------

. regress legparties_xls fragmentation2_xls concentration_xls frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    6.10
                                                       Prob > F      =  0.0011
                                                       R-squared     =  0.3527
                                                       Root MSE      =  1.2425

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~2_xls |  -.0231894   .0108321    -2.14   0.037    -.0448721   -.0015066
concentrat~s |  -.2169059   .3234011    -0.67   0.505    -.8642635    .4304516
frag_conc_~s |   .2154692   .0898954     2.40   0.020      .035524    .3954145
       _cons |   1.538796   .1577479     9.75   0.000      1.22303    1.854563
------------------------------------------------------------------------------

. regress legparties_xls fragmentation2_xls concentration_xls frag2_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  3,    58) =   12.75
       Model |  54.9693612     3  18.3231204           Prob > F      =  0.0000
    Residual |  83.3614341    58  1.43726611           R-squared     =  0.3974
-------------+------------------------------           Adj R-squared =  0.3662
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1989

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~2_xls |  -.0329767   .0111651    -2.95   0.005    -.0553262   -.0106272
concentrat~s |   .1639454   .2046322     0.80   0.426    -.2456704    .5735612
frag2_conc~s |   .0250271   .0060518     4.14   0.000     .0129131     .037141
       _cons |   1.676069   .3311658     5.06   0.000     1.013168    2.338969
------------------------------------------------------------------------------

. regress legparties_xls fragmentation2_xls concentration_xls frag2_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    6.67
                                                       Prob > F      =  0.0006
                                                       R-squared     =  0.3974
                                                       Root MSE      =  1.1989

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~2_xls |  -.0329767   .0126559    -2.61   0.012    -.0583102   -.0076432
concentrat~s |   .1639454   .1601838     1.02   0.310    -.1566972     .484588
frag2_conc~s |   .0250271    .008525     2.94   0.005     .0079625    .0420917
       _cons |   1.676069    .153695    10.91   0.000     1.368415    1.983723
------------------------------------------------------------------------------

. regress legparties_xls fragmentation_xls fragmentation2_xls concentration_xls frag2_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  4,    57) =    4.80
                                                       Prob > F      =  0.0021
                                                       R-squared     =  0.4202
                                                       Root MSE      =  1.1863

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~n_xls |  -.4184839   .3271467    -1.28   0.206    -1.073584     .236616
fragme~2_xls |   .0062964   .0318939     0.20   0.844      -.05757    .0701628
concentrat~s |    .388199   .2844186     1.36   0.178    -.1813394    .9577373
frag2_conc~s |   .0236103   .0084741     2.79   0.007     .0066412    .0405794
       _cons |   2.178643   .4129334     5.28   0.000     1.351758    3.005528
------------------------------------------------------------------------------

. regress legparties_xls fragmentation_xls fragmentation2_xls concentration_xls frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  4,    57) =    5.02
                                                       Prob > F      =  0.0016
                                                       R-squared     =  0.4250
                                                       Root MSE      =  1.1813

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~n_xls |  -.7441366   .3278166    -2.27   0.027    -1.400578   -.0876952
fragme~2_xls |   .0395133   .0290935     1.36   0.180    -.0187454     .097772
concentrat~s |   .0428573   .3682228     0.12   0.908     -.694496    .7802107
frag_conc_~s |   .2380957   .0827804     2.88   0.006     .0723308    .4038605
       _cons |   2.530089   .4117784     6.14   0.000     1.705517    3.354661
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Could not replicate either, but closest one was with            *;
. *       fragmentation2 and frag2_conc.                                  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       Model 3                                                         *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls frag_con
> c_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =   10.63
       Model |  74.2629761     6  12.3771627           Prob > F      =  0.0000
    Residual |  64.0678192    55  1.16486944           R-squared     =  0.5369
-------------+------------------------------           Adj R-squared =  0.4863
       Total |  138.330795    61  2.26771796           Root MSE      =  1.0793

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2352271   .2020602     1.16   0.249    -.1697105    .6401648
proximity_~s |  -2.051959   .5561913    -3.69   0.001    -3.166591   -.9373263
prox_presc~s |   .5577793   .2051628     2.72   0.009     .1466239    .9689347
fragme~n_xls |  -.3319799   .1096906    -3.03   0.004    -.5518047    -.112155
concentrat~s |  -.2903656   .2548284    -1.14   0.259    -.8010531    .2203219
frag_conc_~s |   .2519307   .0588715     4.28   0.000     .1339497    .3699118
       _cons |   2.508043   .3971169     6.32   0.000     1.712203    3.303883
------------------------------------------------------------------------------

. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls frag_con
> c_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    7.82
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5369
                                                       Root MSE      =  1.0793

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2352271   .1932523     1.22   0.229    -.1520591    .6225134
proximity_~s |  -2.051959   .4919239    -4.17   0.000    -3.037796   -1.066121
prox_presc~s |   .5577793   .1700702     3.28   0.002      .216951    .8986075
fragme~n_xls |  -.3319799   .1211154    -2.74   0.008    -.5747005   -.0892592
concentrat~s |  -.2903656   .2971519    -0.98   0.333    -.8858713    .3051401
frag_conc_~s |   .2519307   .0862365     2.92   0.005      .079109    .4247524
       _cons |   2.508043   .3528037     7.11   0.000     1.801009    3.215077
------------------------------------------------------------------------------

. regress legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls frag_conc_
> xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =   10.63
       Model |  74.2635705     6  12.3772618           Prob > F      =  0.0000
    Residual |  64.0672248    55  1.16485863           R-squared     =  0.5369
-------------+------------------------------           Adj R-squared =  0.4863
       Total |  138.330795    61  2.26771796           Root MSE      =  1.0793

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   .1021692   .0877465     1.16   0.249    -.0736787    .2780171
proximity_~s |  -2.051935   .5561897    -3.69   0.001    -3.166564   -.9373057
prox_presc~s |   .5577756   .2051613     2.72   0.009     .1466232     .968928
fragme~n_xls |  -.3319917   .1096909    -3.03   0.004    -.5518171   -.1121662
concentrat~s |  -.2903516   .2548189    -1.14   0.259      -.80102    .2203168
frag_conc_~s |   .2519348   .0588709     4.28   0.000     .1339549    .3699148
       _cons |   2.508003   .3971186     6.32   0.000     1.712159    3.303846
------------------------------------------------------------------------------

. regress legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls frag_conc_
> xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    7.82
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5369
                                                       Root MSE      =  1.0793

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   .1021692   .0839217     1.22   0.229    -.0660137    .2703522
proximity_~s |  -2.051935   .4919231    -4.17   0.000    -3.037771   -1.066099
prox_presc~s |   .5577756   .1700673     3.28   0.002     .2169531    .8985981
fragme~n_xls |  -.3319917    .121115    -2.74   0.008    -.5747115   -.0892718
concentrat~s |  -.2903516   .2971321    -0.98   0.333    -.8858176    .3051143
frag_conc_~s |   .2519348   .0862353     2.92   0.005     .0791155    .4247542
       _cons |   2.508003   .3528011     7.11   0.000     1.800974    3.215032
------------------------------------------------------------------------------

. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag_co
> nc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    9.52
       Model |  70.4772831     6  11.7462139           Prob > F      =  0.0000
    Residual |  67.8535122    55  1.23370022           R-squared     =  0.5095
-------------+------------------------------           Adj R-squared =  0.4560
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1107

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2079852   .2113854     0.98   0.329    -.2156407    .6316111
proximity_~s |  -2.219835   .5660129    -3.92   0.000     -3.35415    -1.08552
prox_presc~s |   .5741542     .21094     2.72   0.009     .1514211    .9968874
fragme~2_xls |  -.0245791    .010405    -2.36   0.022    -.0454312    -.003727
concentrat~s |  -.3468349   .2939045    -1.18   0.243    -.9358327    .2421628
frag_conc_~s |   .2251356   .0616849     3.65   0.001     .1015162     .348755
       _cons |   2.117607   .3720999     5.69   0.000     1.371902    2.863312
------------------------------------------------------------------------------

. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag_co
> nc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.90
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5095
                                                       Root MSE      =  1.1107

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2079852   .2276844     0.91   0.365    -.2483046     .664275
proximity_~s |  -2.219835   .5138513    -4.32   0.000    -3.249616   -1.190054
prox_presc~s |   .5741542   .1721755     3.33   0.002     .2291068    .9192017
fragme~2_xls |  -.0245791   .0127782    -1.92   0.060    -.0501872     .001029
concentrat~s |  -.3468349   .3764304    -0.92   0.361    -1.101218    .4075484
frag_conc_~s |   .2251356   .0986119     2.28   0.026      .027513    .4227582
       _cons |   2.117607    .324436     6.53   0.000     1.467422    2.767791
------------------------------------------------------------------------------

. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag2_c
> onc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =   10.25
       Model |  73.0308741     6  12.1718123           Prob > F      =  0.0000
    Residual |  65.2999212    55   1.1872713           R-squared     =  0.5279
-------------+------------------------------           Adj R-squared =  0.4764
       Total |  138.330795    61  2.26771796           Root MSE      =  1.0896

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2182518   .2059951     1.06   0.294    -.1945716    .6310752
proximity_~s |   -2.00998   .5621323    -3.58   0.001    -3.136519   -.8834421
prox_presc~s |   .5335551    .207773     2.57   0.013     .1171687    .9499415
fragme~2_xls |  -.0320845   .0113122    -2.84   0.006    -.0547546   -.0094144
concentrat~s |   .0906479   .1959151     0.46   0.645    -.3019747    .4832704
frag2_conc~s |   .0243417   .0060868     4.00   0.000     .0121434      .03654
       _cons |   2.138236   .3652728     5.85   0.000     1.406213    2.870259
------------------------------------------------------------------------------

. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag2_c
> onc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.85
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5279
                                                       Root MSE      =  1.0896

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2182518   .1894963     1.15   0.254    -.1615073    .5980109
proximity_~s |   -2.00998   .4976855    -4.04   0.000    -3.007364   -1.012596
prox_presc~s |   .5335551   .1832671     2.91   0.005     .1662796    .9008306
fragme~2_xls |  -.0320845   .0132502    -2.42   0.019    -.0586384   -.0055305
concentrat~s |   .0906479   .1888383     0.48   0.633    -.2877924    .4690882
frag2_conc~s |   .0243417   .0089246     2.73   0.009     .0064564    .0422269
       _cons |   2.138236   .3070175     6.96   0.000     1.522959    2.753512
------------------------------------------------------------------------------

. regress legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag_conc
> _xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    9.52
       Model |  70.4778092     6  11.7463015           Prob > F      =  0.0000
    Residual |  67.8529861    55  1.23369066           R-squared     =  0.5095
-------------+------------------------------           Adj R-squared =  0.4560
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1107

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |     .09034   .0917964     0.98   0.329     -.093624    .2743041
proximity_~s |  -2.219817   .5660113    -3.92   0.000    -3.354129   -1.085505
prox_presc~s |   .5741517   .2109386     2.72   0.009     .1514214    .9968821
fragme~2_xls |  -.0245803   .0104051    -2.36   0.022    -.0454325   -.0037281
concentrat~s |  -.3468328   .2938936    -1.18   0.243    -.9358088    .2421432
frag_conc_~s |   .2251406   .0616845     3.65   0.001     .1015221    .3487591
       _cons |   2.117558   .3721059     5.69   0.000     1.371841    2.863275
------------------------------------------------------------------------------

. regress legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag_conc
> _xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.90
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5095
                                                       Root MSE      =  1.1107

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |     .09034   .0988738     0.91   0.365    -.1078076    .2884876
proximity_~s |  -2.219817    .513852    -4.32   0.000    -3.249599   -1.190034
prox_presc~s |   .5741517   .1721724     3.33   0.002     .2291106    .9191929
fragme~2_xls |  -.0245803   .0127783    -1.92   0.060    -.0501885     .001028
concentrat~s |  -.3468328   .3764058    -0.92   0.361    -1.101167    .4075013
frag_conc_~s |   .2251406    .098611     2.28   0.026     .0275198    .4227614
       _cons |   2.117558   .3244426     6.53   0.000     1.467361    2.767755
------------------------------------------------------------------------------

. regress legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag2_con
> c_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =   10.25
       Model |  73.0314882     6  12.1719147           Prob > F      =  0.0000
    Residual |  65.2993071    55  1.18726013           R-squared     =  0.5279
-------------+------------------------------           Adj R-squared =  0.4765
       Total |  138.330795    61  2.26771796           Root MSE      =  1.0896

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   .0948006   .0894558     1.06   0.294    -.0844727     .274074
proximity_~s |  -2.009956   .5621307    -3.58   0.001    -3.136491   -.8834211
prox_presc~s |   .5335518   .2077715     2.57   0.013     .1171684    .9499352
fragme~2_xls |  -.0320859   .0113122    -2.84   0.006    -.0547562   -.0094157
concentrat~s |   .0906601   .1959077     0.46   0.645    -.3019477    .4832678
frag2_conc~s |   .0243423   .0060868     4.00   0.000      .012144    .0365405
       _cons |   2.138183   .3652783     5.85   0.000     1.406149    2.870217
------------------------------------------------------------------------------

. regress legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag2_con
> c_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.85
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5279
                                                       Root MSE      =  1.0896

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   .0948006   .0822923     1.15   0.254    -.0701168     .259718
proximity_~s |  -2.009956   .4976847    -4.04   0.000    -3.007339   -1.012574
prox_presc~s |   .5335518   .1832639     2.91   0.005     .1662828    .9008208
fragme~2_xls |  -.0320859   .0132503    -2.42   0.019      -.05864   -.0055318
concentrat~s |   .0906601   .1888248     0.48   0.633    -.2877532    .4690733
frag2_conc~s |   .0243423   .0089245     2.73   0.009     .0064571    .0422274
       _cons |   2.138183   .3070213     6.96   0.000     1.522899    2.753468
------------------------------------------------------------------------------

. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag2_c
> onc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.85
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5279
                                                       Root MSE      =  1.0896

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2182518   .1894963     1.15   0.254    -.1615073    .5980109
proximity_~s |   -2.00998   .4976855    -4.04   0.000    -3.007364   -1.012596
prox_presc~s |   .5335551   .1832671     2.91   0.005     .1662796    .9008306
fragme~2_xls |  -.0320845   .0132502    -2.42   0.019    -.0586384   -.0055305
concentrat~s |   .0906479   .1888383     0.48   0.633    -.2877924    .4690882
frag2_conc~s |   .0243417   .0089246     2.73   0.009     .0064564    .0422269
       _cons |   2.138236   .3070175     6.96   0.000     1.522959    2.753512
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *       Could not replicate - but last equation is closest.             *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *                               Model 4                                 *;
. *     ****************************************************************  *;
. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls logmag1
> 0_frag_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    9.02
       Model |  68.6094546     6  11.4349091           Prob > F      =  0.0000
    Residual |  69.7213407    55  1.26766074           R-squared     =  0.4960
-------------+------------------------------           Adj R-squared =  0.4410
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1259

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -1.326105   .4003109    -3.31   0.002    -2.128346   -.5238637
proximity_~s |  -1.888323    .593764    -3.18   0.002    -3.078253   -.6983938
prox_presc~s |   .6364208   .2132434     2.98   0.004     .2090714     1.06377
fragme~n_xls |  -.0816675   .0735476    -1.11   0.272    -.2290602    .0657253
concentrat~s |   .3648297   .1806367     2.02   0.048     .0028256    .7268338
logmag10_f.. |    .154109   .0438206     3.52   0.001     .0662905    .2419276
       _cons |   2.451147   .4179158     5.87   0.000     1.613625    3.288669
------------------------------------------------------------------------------

. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls logmag1
> 0_frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.09
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4960
                                                       Root MSE      =  1.1259

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -1.326105   .5910377    -2.24   0.029    -2.510571   -.1416386
proximity_~s |  -1.888323   .4606799    -4.10   0.000    -2.811547   -.9651002
prox_presc~s |   .6364208   .1621898     3.92   0.000     .3113853    .9614564
fragme~n_xls |  -.0816675   .0586667    -1.39   0.170    -.1992383    .0359033
concentrat~s |   .3648297    .183722     1.99   0.052    -.0033574    .7330167
logmag10_f.. |    .154109   .0731098     2.11   0.040     .0075938    .3006242
       _cons |   2.451147   .4382131     5.59   0.000     1.572948    3.329346
------------------------------------------------------------------------------

. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag
> 10_frag_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    8.74
       Model |  67.5130893     6  11.2521815           Prob > F      =  0.0000
    Residual |   70.817706    55  1.28759466           R-squared     =  0.4881
-------------+------------------------------           Adj R-squared =  0.4322
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1347

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -1.227082   .3974515    -3.09   0.003    -2.023593   -.4305712
proximity_~s |  -1.972116   .5920742    -3.33   0.002     -3.15866    -.785573
prox_presc~s |   .6357803   .2149828     2.96   0.005      .204945    1.066616
fragme~2_xls |  -.0039783   .0066083    -0.60   0.550    -.0172216     .009265
concentrat~s |   .3291766   .1789564     1.84   0.071    -.0294599    .6878132
logmag10_f.. |   .1406661   .0434911     3.23   0.002      .053508    .2278243
       _cons |    2.31455   .3943725     5.87   0.000      1.52421     3.10489
------------------------------------------------------------------------------

. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag
> 10_frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.16
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4881
                                                       Root MSE      =  1.1347

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -1.227082   .5698207    -2.15   0.036    -2.369028   -.0851357
proximity_~s |  -1.972116   .4694402    -4.20   0.000    -2.912895   -1.031337
prox_presc~s |   .6357803   .1666494     3.82   0.000     .3018074    .9697531
fragme~2_xls |  -.0039783   .0039882    -1.00   0.323    -.0119708    .0040142
concentrat~s |   .3291766   .1747835     1.88   0.065    -.0210973    .6794506
logmag10_f.. |   .1406661   .0719661     1.95   0.056    -.0035572    .2848894
       _cons |    2.31455   .3911327     5.92   0.000     1.530703    3.098398
------------------------------------------------------------------------------

. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag
> 10_frag2_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    9.06
       Model |  68.7697641     6  11.4616274           Prob > F      =  0.0000
    Residual |  69.5610312    55  1.26474602           R-squared     =  0.4971
-------------+------------------------------           Adj R-squared =  0.4423
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1246

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -.8391942   .2892597    -2.90   0.005    -1.418884   -.2595047
proximity_~s |  -1.962438   .5860558    -3.35   0.001     -3.13692   -.7879559
prox_presc~s |   .6737227   .2134737     3.16   0.003     .2459118    1.101534
fragme~2_xls |  -.0114913   .0078742    -1.46   0.150    -.0272716     .004289
concentrat~s |   .5351793   .1642795     3.26   0.002     .2059558    .8644027
l~2_conc_xls |   .0157112   .0046043     3.41   0.001      .006484    .0249385
       _cons |   2.095498    .376285     5.57   0.000     1.341406     2.84959
------------------------------------------------------------------------------

. regress  legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag
> 10_frag2_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.06
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4971
                                                       Root MSE      =  1.1246

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -.8391942   .3383754    -2.48   0.016    -1.517314   -.1610747
proximity_~s |  -1.962438   .4535856    -4.33   0.000    -2.871444   -1.053432
prox_presc~s |   .6737227     .17025     3.96   0.000      .332534    1.014911
fragme~2_xls |  -.0114913   .0066349    -1.73   0.089     -.024788    .0018054
concentrat~s |   .5351793   .1787505     2.99   0.004     .1769553    .8934032
l~2_conc_xls |   .0157112   .0073172     2.15   0.036     .0010472    .0303753
       _cons |   2.095498   .3207279     6.53   0.000     1.452745    2.738251
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls logmag_fr
> ag_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    9.02
       Model |  68.6009745     6  11.4334958           Prob > F      =  0.0000
    Residual |  69.7298208    55  1.26781492           R-squared     =  0.4959
-------------+------------------------------           Adj R-squared =  0.4409
       Total |  138.330795    61  2.26771796           Root MSE      =   1.126

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |  -.5757599   .1738611    -3.31   0.002    -.9241852   -.2273345
proximity_~s |  -1.888534   .5937957    -3.18   0.002    -3.078527   -.6985406
prox_presc~s |   .6364581   .2132556     2.98   0.004     .2090843    1.063832
fragme~n_xls |  -.0816388   .0735541    -1.11   0.272    -.2290445    .0657668
concentrat~s |   .3648123   .1806506     2.02   0.048     .0027805    .7268441
logmag_fra.. |   .0669127   .0190326     3.52   0.001     .0287704     .105055
       _cons |   2.451122   .4179642     5.86   0.000     1.613503    3.288741
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation_xls concentration_xls logmag_fr
> ag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.09
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4959
                                                       Root MSE      =   1.126

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |  -.5757599   .2567032    -2.24   0.029    -1.090205   -.0613152
proximity_~s |  -1.888534   .4607008    -4.10   0.000    -2.811799   -.9652687
prox_presc~s |   .6364581   .1622063     3.92   0.000     .3113894    .9615268
fragme~n_xls |  -.0816388   .0586722    -1.39   0.170    -.1992205    .0359428
concentrat~s |   .3648123   .1837283     1.99   0.052    -.0033875    .7330121
logmag_fra.. |   .0669127   .0317548     2.11   0.040     .0032747    .1305507
       _cons |   2.451122   .4382747     5.59   0.000       1.5728    3.329444
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag_f
> rag_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    8.74
       Model |  67.5051151     6  11.2508525           Prob > F      =  0.0000
    Residual |  70.8256802    55  1.28773964           R-squared     =  0.4880
-------------+------------------------------           Adj R-squared =  0.4321
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1348

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |  -.5327542   .1726175    -3.09   0.003    -.8786875   -.1868209
proximity_~s |  -1.972312   .5921032    -3.33   0.002    -3.158913   -.7857109
prox_presc~s |   .6358136   .2149942     2.96   0.005     .2049556    1.066672
fragme~2_xls |  -.0039755   .0066088    -0.60   0.550    -.0172198    .0092688
concentrat~s |   .3291769   .1789708     1.84   0.071    -.0294887    .6878425
logmag_fra.. |   .0610741   .0188893     3.23   0.002     .0232191    .0989291
       _cons |   2.314546   .3944143     5.87   0.000     1.524122     3.10497
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag_f
> rag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.15
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4880
                                                       Root MSE      =  1.1348

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |  -.5327542   .2474872    -2.15   0.036     -1.02873   -.0367787
proximity_~s |  -1.972312   .4694569    -4.20   0.000    -2.913125     -1.0315
prox_presc~s |   .6358136   .1666643     3.81   0.000     .3018108    .9698164
fragme~2_xls |  -.0039755   .0039887    -1.00   0.323     -.011969     .004018
concentrat~s |   .3291769   .1747931     1.88   0.065    -.0211163    .6794701
logmag_fra.. |   .0610741   .0312576     1.95   0.056    -.0015675    .1237156
       _cons |   2.314546   .3911773     5.92   0.000     1.530609    3.098483
------------------------------------------------------------------------------

. gen logmag_frag2_conc_xls = logmag_xls*fragmentation2_xls*concentration_xls;

. label var logmag_frag2_conc_xls "logmag*fragmentation2*concentration";

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag_f
> rag2_conc_xls;

      Source |       SS       df       MS              Number of obs =      62
-------------+------------------------------           F(  6,    55) =    9.06
       Model |  68.7688359     6  11.4614726           Prob > F      =  0.0000
    Residual |  69.5619595    55   1.2647629           R-squared     =  0.4971
-------------+------------------------------           Adj R-squared =  0.4423
       Total |  138.330795    61  2.26771796           Root MSE      =  1.1246

------------------------------------------------------------------------------
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   -.364413   .1256173    -2.90   0.005    -.6161557   -.1126704
proximity_~s |  -1.962518   .5860554    -3.35   0.001    -3.136999   -.7880363
prox_presc~s |   .6737501   .2134747     3.16   0.003     .2459373    1.101563
fragme~2_xls |  -.0114894    .007874    -1.46   0.150    -.0272692    .0042904
concentrat~s |   .5350691     .16428     3.26   0.002     .2058446    .8642936
logmag_fra.. |   .0068232   .0019996     3.41   0.001     .0028158    .0108305
       _cons |    2.09558   .3763001     5.57   0.000     1.341458    2.849702
------------------------------------------------------------------------------

. regress  legparties_xls logmag_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag_f
> rag2_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.06
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4971
                                                       Root MSE      =  1.1246

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logmag_xls |   -.364413   .1469438    -2.48   0.016    -.6588951    -.069931
proximity_~s |  -1.962518   .4535898    -4.33   0.000    -2.871532   -1.053503
prox_presc~s |   .6737501     .17025     3.96   0.000     .3325614    1.014939
fragme~2_xls |  -.0114894   .0066343    -1.73   0.089    -.0247848    .0018059
concentrat~s |   .5350691   .1787317     2.99   0.004     .1768829    .8932554
logmag_fra.. |   .0068232   .0031778     2.15   0.036     .0004546    .0131917
       _cons |    2.09558     .32075     6.53   0.000     1.452783    2.738378
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *      Again, not possible to replicate despite multiple configurations *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *       These are the specifications that get us the closest to the     *;
. *       results shown in Table 2.                                       *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *                               Model 1                                 *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    7.64
                                                       Prob > F      =  0.0002
                                                       R-squared     =  0.2301
                                                       Root MSE      =  1.3551

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .0120857   .1258691     0.10   0.924    -.2398687    .2640401
proximity_~s |  -2.793368   .6398755    -4.37   0.000    -4.074217   -1.512518
prox_presc~s |   .8807476    .207705     4.24   0.000     .4649808    1.296514
       _cons |   2.806523   .4709899     5.96   0.000     1.863735    3.749312
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                               Model 2                                 *;
. *     ****************************************************************  *;
. regress legparties_xls fragmentation2_xls concentration_xls frag2_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  3,    58) =    6.67
                                                       Prob > F      =  0.0006
                                                       R-squared     =  0.3974
                                                       Root MSE      =  1.1989

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~2_xls |  -.0329767   .0126559    -2.61   0.012    -.0583102   -.0076432
concentrat~s |   .1639454   .1601838     1.02   0.310    -.1566972     .484588
frag2_conc~s |   .0250271    .008525     2.94   0.005     .0079625    .0420917
       _cons |   1.676069    .153695    10.91   0.000     1.368415    1.983723
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                               Model 3                                 *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls frag2_c
> onc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.85
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5279
                                                       Root MSE      =  1.0896

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .2182518   .1894963     1.15   0.254    -.1615073    .5980109
proximity_~s |   -2.00998   .4976855    -4.04   0.000    -3.007364   -1.012596
prox_presc~s |   .5335551   .1832671     2.91   0.005     .1662796    .9008306
fragme~2_xls |  -.0320845   .0132502    -2.42   0.019    -.0586384   -.0055305
concentrat~s |   .0906479   .1888383     0.48   0.633    -.2877924    .4690882
frag2_conc~s |   .0243417   .0089246     2.73   0.009     .0064564    .0422269
       _cons |   2.138236   .3070175     6.96   0.000     1.522959    2.753512
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                               Model 4                                 *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prox_prescandidate_xls fragmentation2_xls concentration_xls logmag1
> 0_frag2_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  6,    55) =    6.06
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4971
                                                       Root MSE      =  1.1246

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |  -.8391942   .3383754    -2.48   0.016    -1.517314   -.1610747
proximity_~s |  -1.962438   .4535856    -4.33   0.000    -2.871444   -1.053432
prox_presc~s |   .6737227     .17025     3.96   0.000      .332534    1.014911
fragme~2_xls |  -.0114913   .0066349    -1.73   0.089     -.024788    .0018054
concentrat~s |   .5351793   .1787505     2.99   0.004     .1769553    .8934032
logmag10_f.. |   .0157112   .0073172     2.15   0.036     .0010472    .0303753
       _cons |   2.095498   .3207279     6.53   0.000     1.452745    2.738251
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *                       Correct specifications                          *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *     ****************************************************************  *;
. *                               Model 1                                 *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prescandidate_xls prox_prescandidate_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  4,    57) =    7.31
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4490
                                                       Root MSE      =  1.1564

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |    .139094   .1071066     1.30   0.199    -.0753833    .3535713
proximity_~s |  -1.235276   .4635068    -2.67   0.010    -2.163433     -.30712
prescandid~s |   .5981868   .1853508     3.23   0.002     .2270281    .9693454
prox_presc~s |   .1407879   .2927324     0.48   0.632    -.4453987    .7269744
       _cons |   1.463066   .2340379     6.25   0.000     .9944137    1.931719
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                               Model 2                                 *;
. *     ****************************************************************  *;
. regress legparties_xls fragmentation_xls fragmentation2_xls concentration_xls frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  4,    57) =    5.02
                                                       Prob > F      =  0.0016
                                                       R-squared     =  0.4250
                                                       Root MSE      =  1.1813

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
fragme~n_xls |  -.7441366   .3278166    -2.27   0.027    -1.400578   -.0876952
fragme~2_xls |   .0395133   .0290935     1.36   0.180    -.0187454     .097772
concentrat~s |   .0428573   .3682228     0.12   0.908     -.694496    .7802107
frag_conc_~s |   .2380957   .0827804     2.88   0.006     .0723308    .4038605
       _cons |   2.530089   .4117784     6.14   0.000     1.705517    3.354661
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                               Model 3                                 *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prescandidate_xls prox_prescandidate_xls fragmentation_xls concentr
> ation frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F(  7,    54) =    8.52
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.6882
                                                       Root MSE      =  .89372

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .3327218   .1242238     2.68   0.010     .0836681    .5817755
proximity_~s |   -.844499   .4584812    -1.84   0.071    -1.763699    .0747004
prescandid~s |   .5387258   .1880399     2.86   0.006     .1617286     .915723
prox_presc~s |  -.0264995   .2960443    -0.09   0.929    -.6200326    .5670337
fragme~n_xls |  -.2507962   .0992787    -2.53   0.014    -.4498381   -.0517543
concentrat~s |  -.5337437   .1949731    -2.74   0.008    -.9246411   -.1428462
frag_conc_~s |   .2389059   .0619676     3.86   0.000     .1146685    .3631434
       _cons |   1.453412   .2772827     5.24   0.000     .8974941    2.009331
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                               Model 4                                 *;
. *     ****************************************************************  *;
. regress legparties_xls logmag10_xls proximity_xls prescandidate_xls prox_prescandidate_xls fragmentation_xls concentr
> ation_xls
> frag_conc_xls logmag10_frag_xls logmag10_conc_xls logmag10_frag_conc_xls, robust;

Regression with robust standard errors                 Number of obs =      62
                                                       F( 10,    51) =   17.38
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.7519
                                                       Root MSE      =  .82029

------------------------------------------------------------------------------
             |               Robust
legparties~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
logmag10_xls |   .6231262   .4729289     1.32   0.194    -.3263181    1.572571
proximity_~s |  -.6031644   .4375756    -1.38   0.174    -1.481634    .2753053
prescandid~s |   .4966268   .1799312     2.76   0.008     .1353999    .8578538
prox_presc~s |   .0526415   .2697411     0.20   0.846    -.4888863    .5941693
fragme~n_xls |  -.3447567   .1360734    -2.53   0.014    -.6179355    -.071578
concentrat~s |   .0819886   .2804282     0.29   0.771    -.4809945    .6449717
frag_conc_~s |   .1659694   .0560291     2.96   0.005     .0534863    .2784525
l~0_frag_xls |  -.0549349   .1229295    -0.45   0.657    -.3017262    .1918565
logmag10_c~s |  -.8553275   .3809406    -2.25   0.029    -1.620098   -.0905573
logmag10_f.. |   .1725761   .0993097     1.74   0.088    -.0267965    .3719487
       _cons |   1.322835    .316875     4.17   0.000     .6866815    1.958988
------------------------------------------------------------------------------

. *     ****************************************************************  *;
. *                       End of basic replication                        *;
. *     ****************************************************************  *;
. log close;
       log:  Z:\interactionmodels\replication\legislativeparties_replication_xls.log
  log type:  text
 closed on:  10 Jan 2007, 20:01:06
-----------------------------------------------------------------------------------------------------------------------
